passt: Probability Associator Time (PASS-T)
Simulates judgments of frequency and duration based on
the Probability Associator Time (PASS-T) model. PASS-T is a memory
model based on a simple competitive artificial neural network. It
can imitate human judgments of frequency and duration, which have
been extensively studied in cognitive psychology
(e.g. Hintzman (1970) <doi:10.1037/h0028865>, Betsch et al. (2010)
<https://psycnet.apa.org/record/2010-18204-003>). The PASS-T model
is an extension of the PASS model (Sedlmeier, 2002,
ISBN:0198508638). The package provides an easy way to run
simulations, which can then be compared with empirical data in
human judgments of frequency and duration.
Version: |
0.1.3 |
Imports: |
magrittr, methods, dplyr, tidyr, rlang |
Suggests: |
knitr, ggplot2, plyr, testthat (≥ 2.1.0), covr, markdown, rmarkdown |
Published: |
2021-05-03 |
DOI: |
10.32614/CRAN.package.passt |
Author: |
Johannes Titz [aut, cre] |
Maintainer: |
Johannes Titz <johannes.titz at gmail.com> |
BugReports: |
https://github.com/johannes-titz/passt/issues |
License: |
GPL-3 |
URL: |
https://github.com/johannes-titz/passt |
NeedsCompilation: |
no |
Materials: |
NEWS |
CRAN checks: |
passt results |
Documentation:
Downloads:
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